PM2.5 data reliability, consistency, and air quality assessment in five Chinese cities

Xuan Liang, Shuo Li, Shuyi Zhang, Hui Huang, Song Xi Chen

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52 Citations (Scopus)


We investigate particulate matter (PM2.5) data reliability in five major Chinese cities: Beijing, Shanghai, Guangzhou, Chengdu, and Shenyang by cross-validating data from the U.S. diplomatic posts and the nearby Ministry of Environmental Protection sites based on 3 years' data from January 2013. The investigation focuses on the consistency in air quality assessment derived from the two data sources. It consists of studying (i) the occurrence length and percentage of different PM2.5 concentration ranges; (ii) the air quality assessment for each city; and (iii) the winter-heating effects in Beijing and Shenyang. Our analysis indicates that the two data sources produced highly consistent air quality assessment in the five cities. This is encouraging as it would inject a much needed confidence on the air pollution measurements from China. We also provide air quality assessments on the severity and trends of the fine particulate matter pollution in the five cities. The assessments are produced by statistically constructing the standard monthly meteorological conditions for each city, which are designed to minimize the effects of confounding factors due to yearly variations of some important meteorological variables. Our studies show that Beijing and Chengdu had the worst air quality, while Guangzhou and Shanghai faired the best among the five cities. Most of the five cities had their PM2.5 concentration decreased significantly in the last 2 years. By linking the air quality with the amount of energy consumed, our study suggests that the geographical configuration is a significant factor in a city's air quality management and economic development.

Original languageEnglish
Pages (from-to)10220-10236
Number of pages17
JournalJournal of Geophysical Research: Atmospheres
Issue number17
Publication statusPublished - 16 Sep 2016
Externally publishedYes


  • air quality assessment
  • data quality
  • heating effect
  • meteorological effects
  • PM2.5
  • statistical modeling

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